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Train Often, Deploy Selectively: Forward-Gated Model Replacement in

https://arxiv.org/html/2607.28577v1
org perpetual non-exclusive license arXiv:2607

Report GitHub Issue

https://arxiv.org/html/2608.03358v1
org perpetual non-exclusive license arXiv:2608

Probing Character-level Transformers for the Spanish L-shaped Morphome

https://arxiv.org/html/2608.03452v1
2 Membership is decodable beyond the surface forms 4

Coordinated Primary Frequency Regulation and Grid-Forming Control for

https://arxiv.org/html/2608.02813v1
Yufei Xi and Lin Cheng are with the State Key Laboratory of Power System Operation and Control (Department of Electrical Engineering, Tsinghua University), Beijing 100084, China Florian Döfler is with the Automatic Control Laboratory, ETH Zürich, 8092 Zürich, Switzerland Abstract Conventional grid-forming (GFM)

Consensus Measures for Unstructured Biomedical Text Annotations

https://arxiv.org/html/2608.03529v1
ch Abstract Biomedical literature is increasingly mined for knowledge beyond the questions it was written to answer

Mapping the City Through the Lens of Language Models

https://arxiv.org/html/2608.02971v1
In geographic settings, this behavior is consequential because the category city spans substantial variation in scale, form, infrastructure, ecology, function, and development

On the Diversity of Analogy Making in Large Language Models

https://arxiv.org/html/2608.03233v1
org perpetual non-exclusive license arXiv:2608

Efficient Audio Enhancement with a Differentiable Psychoacoustic Loss

https://arxiv.org/html/2608.02918v1
org perpetual non-exclusive license arXiv:2608

Towards Real-world Environment-aware Zero-shot Text-to-speech Synthesis

https://arxiv.org/html/2608.03011v1
org perpetual non-exclusive license arXiv:2608

Activation-Guided Neuron Intervention to Induce Alzheimer’s-Related

https://arxiv.org/html/2608.03067v1
Beyond their use as predictors, pretrained language models have also become tools for examining how linguistic information is organized in internal representations that can support AD prediction (Balagopalan et al

Report GitHub Issue

https://arxiv.org/html/2608.03545v1
org perpetual non-exclusive license arXiv:2608

1. Introduction

https://arxiv.org/html/2608.02909v1
This approach is theoretically valid, easy to implement, and does not require new data

What Language Does and What the Evidence Supports: A Functional Role

https://arxiv.org/html/2608.03099v1
2 Inspectable Language Is Not Necessarily Correct or Used 5

Guarding a Target Area from a Heterogeneous Group of Cooperative

https://arxiv.org/html/2407.00762v1
The objective of the attacker team is to jointly minimize the weighted sum of their final levels of proximity to the target area, whereas the defender aims to maximize the same value

Decoupling Generation and Selection for Budget-Constrained Faithful

https://arxiv.org/html/2608.03655v1
org perpetual non-exclusive license arXiv:2608

Learning to Control Unknown Strongly Monotone Games

https://arxiv.org/html/2407.00575v3
Ilai Bistritz is with the Department of Industrial Engineering and the School of Electrical Engineering, Tel Aviv Univeristy, Israel

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https://arxiv.org/pdf/2102.13654
üðƒ48#¼vBB¯Òˆ mÅt÷ž={vêÔ Ö³ðĉ{ôèÁWüËk»ví¨À_ªrOR£°²u•>˜ÖüÕüÅÅÅYSÃ\+V,·™ÍßLqO€8µ--”ÛégÏžMq¼––ÛJLLTùwîÜÉÙv²ðÍ›7Ožß·o_pp°8M„ÿíÒ¥ ÷³Ï>ƒ¼°¸uëÖ¼©S§Nƒ úõëÇ+V,]ºôk¯½V¹re ; y‹)‚ñ„¿€põÕWò[Y'0õõõÅA�=zøðáxX,Ÿ={V…àf‡­E‡$0’Q[ºJÍH‚Å*4Z¾|ùìdñ¦oß¾

When Collaboration Becomes a Trigger:Collective Evidence-Threshold

https://arxiv.org/html/2608.01085v1
org perpetual non-exclusive license arXiv:2608

Testing the effects of an unobservable factor: Do marriage prospects

https://arxiv.org/html/2410.19947v2
org perpetual non-exclusive license arXiv:2410

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Su is with the School of Cyber Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, China (E-mail: zhousu@ieee

You’ve Got to be Efficient: Ambiguity, Misspecification and

https://arxiv.org/html/2604.05327v4
Any researcher or decision-maker who relies on a statistical model to learn about a parameter of interest must therefore contend with the possibility that the likelihood is misspecified

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
This version is a work in progress; please feel free to contact me if you find a mistake, think I missed an important contribution, or just want to send a comment

Effort-Centric Fairness in Lending Decisions

https://arxiv.org/html/2607.28847v1
A parallel and increasingly intertwined regulatory concern is the explainability of automated credit decisions

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https://arxiv.org/src/2405.20232
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https://arxiv.org/pdf/2608.04008
Ù6¨¦ãþ ¬>Ÿ–£þÇÈŒ6=RBmL”õ·LXƇÄM¤_³|¼èÉöVõN‡eÑï]Vƒñ¨Ð[ÁRóªÒ{‚ñ5X68$T§å÷ž…­`=�ªŒì™"ÿ03[‚Rô/u‰ Cƒ*ÌJ¬³sI)u–8ƒW“qÿMI|�WGÏ0hù©Z5+ÆÞ§l*¢ pƒair 3÷zÝ } ÃBx×�ŠJ ê±ß£²ºóÛ¡jÞy Ń£‹ŠE"eSPL0¯Š}O;ï®�¾kã;ï_žþEØëø¢æ»³6ó"®)´º†sºr„›\#÷¢êU¥xtôƒ÷’Q‚ é í÷2~'åw�grã‰xô¢W]ÇÕpp*þc …¾ÿ)>VÕåô‡NçbQWŒ'ç�óZŸ]

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https://arxiv.org/pdf/2607.26405v1
e„­¥âŒ8äúò¤Îs`ÚWg+`î#)�SÎ%~Æü8§NTâ°ÒŒ¡YEð,Ê ¯(îÒ6À*†3FÓª¼r44ëP#®Y§†fÍžhhÓ°CkE8ã8å²+ûj®"7Gö9ç¢~PpúCŠ+ªRî2C�ËÇ#`øp¿Ëœ1q îE—Œ‡£ü�ˆEÈ5’=„ŸF]=7úz&`ÿq•p&b¡Ã°§|Ç _/ôcØS‰½MrõÎ¤× fÈ/öÝðù%Ðm ÆðȰw öŠù\Ô‰CÞúbÖ“ ÿxö5cÖ fÌw(¥:¤§ÐKœŸz‰gßqf1iXgù·á3NpÆ óéìÓy/hHS>Wø›ÎúÁÏ#ÊÍÁ/—«ù¯¡¿ÿ5fÒerT§apC…

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https://arxiv.org/pdf/2006.15704
i'n;‘„¦¡õrãµHfãÄa‚»Ï…"÷X�XÒbôVþW*¨àéìf·µ»ÌÊŒøöT‘”«îÇ�G¡’yUÃçisÿÜ„²¤Ëä8½®]]õý¦•ÿý§f“ãDžvmÃlçùþ±+O•“‹�šË3¾UWž¤¼…ÿ“Ć®ÍiÇ

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https://arxiv.org/pdf/2608.03709
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https://arxiv.org/src/2608.03883
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https://arxiv.org/src/2006.01128
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